SSN: learning sparse switchable normalization via SparsestMax

DOI10.1007/s11263-019-01269-yzbMath1483.68346arXiv1903.03793OpenAlexW3000218820MaRDI QIDQ2056134

Ruimao Zhang, Ping Luo, Wenqi Shao, Jiamin Ren, Jingyu Li, Xiao-Gang Wang

Publication date: 1 December 2021

Published in: International Journal of Computer Vision (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1903.03793

zbMATH Keywords

classificationoptimizationnormalizationdeep learning

Mathematics Subject Classification ID

Artificial neural networks and deep learning (68T07)

Related Items

Adaptively Sparse Transformers Hawkes Process

Uses Software

• SPGL1
• DeepLab
• PyTorch
• GitHub
• Detectron
• MS-COCO
• ArcFace
• DARTS
• Cityscapes
• ADE20k
• MegaFace
• ShuffleNet
• Inception-v4
• SNAS
• Faster R-CNN

Cites Work

• Fast projection onto the simplex and the \(l_1\) ball
• Multilayer feedforward networks are universal approximators
• Probing the Pareto Frontier for Basis Pursuit Solutions
• Validation of subgradient optimization